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Machine Learning Algorithms: Selection of Appropriate Validation Populations for Cardiology Research-Be Careful!

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Title: Machine Learning Algorithms: Selection of Appropriate Validation Populations for Cardiology Research-Be Careful!
Authors: Sanders WE Jr; CorVista Health, Inc, Washington, DC, USA; University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Electronic address: wsanders@corvista.com., Khedraki R; Scripps Clinic, San Diego, California, USA., Rabbat M; Loyola University Medical Center, Maywood, Illinois, USA., McMinn TR; Austin Heart, Austin, Texas, USA., Burton T; CorVista Health(†), Toronto, Ontario, Canada., Khosousi A; CorVista Health(†), Toronto, Ontario, Canada., Fathieh F; CorVista Health(†), Toronto, Ontario, Canada., Gillins HR; CorVista Health, Inc, Washington, DC, USA., Ramchandani S; CorVista Health(†), Toronto, Ontario, Canada., Shadforth IP; CorVista Health, Inc, Washington, DC, USA.
Source: JACC. Advances [JACC Adv] 2023 Jan 11; Vol. 2 (1), pp. 100166. Date of Electronic Publication: 2023 Jan 11 (Print Publication: 2023).
Publication Type: Editorial
Journal Info: Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918419284106676 Publication Model: eCollection Cited Medium: Internet ISSN: 2772-963X (Electronic) Linking ISSN: 2772963X NLM ISO Abbreviation: JACC Adv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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